Research Article | OPEN ACCESS
Application of EM Algorithm in Statistics Natural Language Processing
Xuexia Gao and Yun Wang
Computer and Information Engineering College, Xinxiang University, Xinxiang 453000, China
Research Journal of Applied Sciences, Engineering and Technology 2013 10:2969-2973
Received: September 16, 2012 | Accepted: October 31, 2012 | Published: March 25, 2013
Abstract
This study describes the basic framework of EM algorithm and gives how to apply EM algorithm to solve the problem of maximum-likelihood parameters estimation combining with the models of HMM and PCFG. In the process of statistics natural language, one kind of problem is often encountered that is how to solve the parameter's maximum-likelihood estimation when observation data is incomplete. EM algorithm is the classical method to solve this problem. Finally, the advantages and disadvantages of EM algorithm are discussed.
Keywords:
Context-free grammar, EM algorithm, hidden Markov model, likelihood function, natural language, parameter estimation,
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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